Current autonomous driving path planning interface between an autonomous driving controller and a powertrain controller is a simple powertrain torque (or vehicle longitudinal acceleration/deceleration request) at a current point in time. This is a similar type of interface to the powertrain controller as compared to a cruise control system, and may lead to inefficient vehicle path planning if the vehicle path planning does not take into consideration the efficiency of the powertrain components, such as traction drive, high voltage energy storage system, thermal management, or (in the case of a conventional powertrain system) the internal combustion engine, etc. Typical autonomous vehicle path planning algorithms output a target vehicle acceleration (or wheel torque) request during the autonomous driving maneuver at the current vehicle operating state without inputs for current or future (or predictive) knowledge of the efficiency of the powertrain components for the desired vehicle trajectory.
Accordingly, there exists a need for a strategy for predicting the efficiency of various powertrain components, and optimize the autonomous driving path of the vehicle based on the efficiency of the powertrain components, where there is an optimized powertrain control strategy for acceleration/deceleration control of a fully autonomous or semi-autonomous driving vehicle.